Quantitative Trading Analyst

Five Dimensions Energy LLC; Princeton (NJ); On-site; USD 90,000 - 140,000; Full time

Benefits offered by this job

Close mentorship

Agile team

Direct impact

Opportunities for growth

Job summary

Five Dimensions Energy is seeking a Quantitative Trading Analyst to work across the full research-to-trading cycle in North American wholesale power markets. You will formulate hypotheses, assemble datasets, design and validate predictive models, and optimize bidding models for live trading workflows.

Responsibilities include backtesting, data cleaning, and evaluating ideas to improve future models and strategies, with Python and SQL as primary tools and a willingness to learn production data

Responsibilities

• Representive problems include price forecasting, generation forecasting, fundamental power-market analysis, optimization, and portfolio construction.
• The work requires statistical thinking and understanding of physical market dynamics – load, generation, outages, transmission, weather, and participant behaviours.
• Python and SQL are the primary tools for research and data analysis.

Job description

At Five Dimensions Energy, research and trading are tightly integrated. We develop systematic strategies for North American wholesale power markets by combining quantitative modeling, fundamental market understanding, and feedback from live trading. Every member of the team is expected to code, conduct research, and develop the judgment needed to trade. As a Quantitative Trading Analyst, you will work across the full research-to-trading cycle. You will formulate hypotheses, assemble and clean datasets, design, build and validate predictive models, and optimize bidding models. You will evaluate ideas through rigorous backtesting and out-of-sample analysis, implement successful research in live workflows, and study actual trading results to improve the next generation of models and strategies.

• Location: Princeton, NJ
• Experience Level: Entry
• Schedule: Full time
• Industry: Energy Trading / Hedge Fund
• Application Deadline: Rolling

Core Responsibilities

• As a Quantitative Trading Analyst, you will work across the full research-to-trading cycle. You will formulate hypotheses, assemble and clean datasets, design, build and validate predictive models, and optimize bidding models. You will evaluate ideas through rigorous back testing and out-of-sample analysis, implement successful research in live workflows, and study actual trading results to improve the next generation of models and strategies.
• Representative problems include price forecasting, generation forecasting, fundamental power-market analysis, optimization, and portfolio construction. The work requires both statistical thinking and a willingness to understand physical market dynamics – including load, generation, outages, transmission, weather, and participant behaviors.
• Python and SQL are the primary tools for research and data analysis. You will be expected to write clear, testable code and to take useful research beyond an exploratory notebook into reliable scheduled or live workflows on shared servers. We do not expect you to arrive as a software engineer or infrastructure specialist; you should be able and willing to learn the practical tools needed to put your work into production.
• You will take direct ownership of research that can influence live trading decisions and, as your experience develops, assume increasing responsibility for strategies, positions, and risk. The long-term goal is to develop systematic trading strategies and use real market experience to make the overall system better.

Qualifications

• A master’s degree in mathematics, statistics, physics, engineering, economics, operations research, data science, computer science, or another rigorous quantitative field. A computer science degree is not required.
• Strong quantitative reasoning grounded in probability, statistics, and empirical model evaluation.
• Strong programming fundamentals, including the ability to solve nontrivial algorithmic and data-processing problems and write clear, testable code.
• Working knowledge of SQL and relational data, or the ability to become productive with them quickly.
• The ability to structure an open-ended research question and move independently from hypothesis to data, evidence, implementation, and iteration.
• Curiosity, intellectual honesty, attention to detail, and a willingness to revise a view when the evidence disagrees.
• Clear written and verbal communication, good judgment, and the ability to collaborate while taking ownership of individual work.
• The ability and motivation to learn unfamiliar technical tools, quantitative methods, and power-market concepts quickly.

What Makes it Sweeter

experience with time-series forecasting, machine learning, optimization, large real-world datasets, power markets, commodities, or trading. Familiarity with Git, Linux, Docker, cloud platforms, database design, or production data workflows is useful, but these are learnable tools rather than selection screens.

What We Offer

• Close mentorship from experienced traders and researchers, with hands-on guidance, frequent feedback, and meaningful responsibility from the beginning.
• The opportunity and excitement of joining an enthusiastic, agile team, where decisions are made quickly, ideas can be tested without unnecessary bureaucracy, and your work has a direct and visible impact on the business.
• The freedom to formulate your own questions and pursue the answers. We want you to do more than complete assigned analyses. You will be encouraged to identify important problems, develop hypotheses, design your own research, and follow the evidence toward better models and trading decisions.
• Exposure to the full research-to-trading process, including data analysis, feature development, forecasting, backtesting, strategy implementation, and learning from live market performance.
• A collaborative and intellectually open environment where ideas are discussed honestly, assumptions are challenged, and team members learn from one another.
• A steep learning curve and significant room for growth across quantitative research, power-market fundamentals, systematic strategy development, and trading.